LlamaParse

Headlines · 3

1. 6d
   LlamaParse adds self-hosted enterprise deployment options

   LlamaIndex announced that LlamaParse can now run in customers’ AWS, Azure, or Google Cloud accounts, or on Kubernetes in their own data centers. Enterprise plans include self-hosting, with deployment teams able to use their own model providers, host supported models on local GPUs, or delegate inference management to LlamaIndex. The vendor says Parse Cost-Effective and Agentic should maintain the same quality with locally hosted document models, while Extract results may vary when deployments use different frontier models.

   LlamaIndex Blog · 🔥 0
2. Nov 2
   LlamaIndex reports nearly 10x faster token generation for OCRia-1 on one B200

   LlamaIndex reports that its optimizations raised OCRia-1 token generation from about 285 to 2,800 tokens per second on a single NVIDIA B200 GPU, a vendor-reported result not independently verified here. The stack combines workload-aware mixed-precision quantization, DFlash2 speculative decoding, ReplaySSM, custom kernels and 17 additional optimizations. LlamaIndex says OCRia-1 is available through LlamaParse across all tiers and plans to contribute generally applicable improvements to vLLM.

   LlamaIndex Blog · 🔥 0
3. Oct 22
   LlamaIndex launches 4B document parsing model OCRia-1

   LlamaIndex introduced OCRia-1, a 4-billion-parameter vision-language model designed to reconstruct complex document tables, charts, formatting and mathematical notation. The developer reports that it scored 87.4 on ParseBench and led table evaluations on olmOCR-bench, PulseBench-Tab and fr-bench-pdf2md, and the model is now integrated into LlamaParse without a pricing change.

   LlamaIndex Blog · 🔥 0

Experience and discussion from the community

Share my LlamaParse experienceAsk about LlamaParse